| OS version | Arch | File Host | Size | Download Link | Rate Limits |
|---|---|---|---|---|---|
| Windows 1.0 | 8086 | Winworld (Kansas City, Missouri) | 541KB | Download | ❌ Yes, 25 per day |
| Windows 2.0 | 386 | Winworld (Kansas City, Missouri) | 2.80MB | Download | ❌ Yes, 25 per day |
| Windows 3.0 | 8086/386 |
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Hello manufacturer. Good device. But software we want to customize. If you allow, we will buy more.
Despite being advertised as "4K 1080P", it really downscales those to 720P.
But for 28.50 EUR from Amazon Warehuose Germany in 2025, one can't exactly complain. https://www.amazon.de/dp/B0DSP74YQW
Chengdu Hotack Technology Co., Ltd. is the OEM?
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
| #!/bin/bash | |
| # Install GNS3 to a LXC Debian 11 container | |
| # Debian 11 Prerequisites: sudo | |
| # Add into the LXC configuration file on Proxmox host (ie. /etc/pve/lxc/<id>.conf) | |
| #lxc.cgroup.devices.allow: c 10:232 rwm | |
| #lxc.cgroup2.devices.allow: c 10:232 rwm | |
| # Also, check that nested and mknod are enabled: | |
| #features: mknod=1,nesting=1 | |
| # Then, in LXC container, type: | |
| #mknod /dev/kvm c 10 232 |
| <!DOCTYPE html> | |
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8" /> | |
| <meta name="viewport" content="width=device-width, initial-scale=1" /> | |
| <title>Privacy Policy · Recruiter Inbox</title> | |
| <style> | |
| body { | |
| margin: 0; | |
| font: 16px/1.6 system-ui, sans-serif; |
As a security professional, it is important to conduct a thorough reconnaissance. With the increasing use of APIs nowadays, it has become paramount to keep access tokens and other API-related secrets secure in order to prevent leaks. However, despite technological advances, human error remains a factor, and many developers still unknowingly hardcode their API secrets into source code and commit them to public repositories. GitHub, being a widely popular platform for public code repositories, may inadvertently host such leaked secrets. To help identify these vulnerabilities, I have created a comprehensive search list using powerful search syntax that enables the search of thousands of leaked keys and secrets in a single search.
(path:*.{File_extension1} OR path:*.{File_extension-N}) AND ({Keyname1} OR {Keyname-N}) AND (({Signature/pattern1} OR {Signature/pattern-N}) AND ({PlatformTag1} OR {PlatformTag-N}))
**1.
Bluesky has implemented age verification measures in response to regional laws that restrict access, prompting users to verify their age through Epic Games' Kids Web Services before they can access adult content.
This sucks, but thankfully there are ways to work around it.
Before diving in: I encourage you to read this entire document, including the
| #NoTrayIcon | |
| #AutoIt3Wrapper_UseX64=y | |
| Opt("MustDeclareVars", 1) | |
| Opt("GUIOnEventMode", 0) | |
| Opt("GUIEventOptions", 1) | |
| #include <GUIConstantsEx.au3> | |
| #include <WindowsConstants.au3> | |
| #include <EditConstants.au3> |
